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$max - Amazon DocumentDB

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$max

$max聚合运算符返回一组文档中指定字段的最大值。此运算符可用于查找一组文档中的最大值。

参数

  • expression:用于计算最大值的表达式。

示例(MongoDB Shell)

以下示例演示如何使用$max运算符在一组学生文档中查找最高分数。该$group阶段将所有文档组合在一起,$max运算符用于计算所有文档中该score字段的最大值。

创建示例文档

db.students.insertMany([ { name: "John", score: 85 }, { name: "Jane", score: 92 }, { name: "Bob", score: 78 }, { name: "Alice", score: 90 } ])

查询示例

db.students.aggregate([ { $group: { _id: null, maxScore: { $max: "$score" } } }, { $project: { _id: 0, maxScore: 1 } } ])

输出

[ { maxScore: 92 } ]

窗口运算符用法示例(MongoDB Shell)

8.0.2 版中的新内容。

该$max操作员还可以在$setWindowFields舞台中用作窗口操作员。在这种情况下,它返回每个窗口中文档的最大值。您可以在output字段下指定运算符,也可以选择使用window文档定义窗口边界。

注意

在中用作窗口运算符时$setWindowFields,中间数据限制$max为 100 MB。超过此限制的操作会返回错误。

创建示例文档

db.stockPrices.insertMany([ { _id: 1, ticker: "ABC", hour: 1, price: 50 }, { _id: 2, ticker: "ABC", hour: 2, price: 45 }, { _id: 3, ticker: "ABC", hour: 3, price: 60 }, { _id: 4, ticker: "ABC", hour: 4, price: 40 }, { _id: 5, ticker: "XYZ", hour: 1, price: 30 }, { _id: 6, ticker: "XYZ", hour: 2, price: 35 }, { _id: 7, ticker: "XYZ", hour: 3, price: 25 } ]);

查询示例

以下示例按分区对文档进行ticker分区hour,按分区排序,并返回从分区开始到当前文档的最高价格。

db.stockPrices.aggregate([ { $setWindowFields: { partitionBy: "$ticker", sortBy: { hour: 1 }, output: { highestSoFar: { $max: "$price", window: { documents: ["unbounded", "current"] } } } } } ]);

输出

[ { "_id": 1, "ticker": "ABC", "hour": 1, "price": 50, "highestSoFar": 50 }, { "_id": 2, "ticker": "ABC", "hour": 2, "price": 45, "highestSoFar": 50 }, { "_id": 3, "ticker": "ABC", "hour": 3, "price": 60, "highestSoFar": 60 }, { "_id": 4, "ticker": "ABC", "hour": 4, "price": 40, "highestSoFar": 60 }, { "_id": 5, "ticker": "XYZ", "hour": 1, "price": 30, "highestSoFar": 30 }, { "_id": 6, "ticker": "XYZ", "hour": 2, "price": 35, "highestSoFar": 35 }, { "_id": 7, "ticker": "XYZ", "hour": 3, "price": 25, "highestSoFar": 35 } ]

每个文档都添加了highestSoFar,即其分区price内运行的最大值,直至包括当前文档。

代码示例

要查看使用$max运算符的代码示例,请选择要使用的语言的选项卡。以下示例显示了累加器的用法(输入$group)和窗口运算符的用法(输入$setWindowFields):

Node.js
const { MongoClient } = require('mongodb'); async function example() { const client = await MongoClient.connect('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false'); const db = client.db('test'); // Accumulator usage: maximum value across a group const students = db.collection('students'); await students.insertMany([ { name: "John", score: 85 }, { name: "Jane", score: 92 }, { name: "Bob", score: 78 }, { name: "Alice", score: 90 } ]); const accumulatorResult = await students.aggregate([ { $group: { _id: null, maxScore: { $max: "$score" } } } ]).toArray(); console.log('Accumulator result:', accumulatorResult); // Window operator usage: running maximum within each partition const stockPrices = db.collection('stockPrices'); await stockPrices.insertMany([ { _id: 1, ticker: "ABC", hour: 1, price: 50 }, { _id: 2, ticker: "ABC", hour: 2, price: 45 }, { _id: 3, ticker: "ABC", hour: 3, price: 60 }, { _id: 4, ticker: "ABC", hour: 4, price: 40 }, { _id: 5, ticker: "XYZ", hour: 1, price: 30 }, { _id: 6, ticker: "XYZ", hour: 2, price: 35 }, { _id: 7, ticker: "XYZ", hour: 3, price: 25 } ]); const windowResult = await stockPrices.aggregate([ { $setWindowFields: { partitionBy: "$ticker", sortBy: { hour: 1 }, output: { highestSoFar: { $max: "$price", window: { documents: ["unbounded", "current"] } } } } } ]).toArray(); console.log('Window result:', windowResult); await client.close(); } example();
Python
from pymongo import MongoClient def example(): client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false') db = client['test'] # Accumulator usage: maximum value across a group students = db.students students.insert_many([ { "name": "John", "score": 85 }, { "name": "Jane", "score": 92 }, { "name": "Bob", "score": 78 }, { "name": "Alice", "score": 90 } ]) accumulator_result = list(students.aggregate([ { "$group": { "_id": None, "maxScore": { "$max": "$score" } } } ])) print('Accumulator result:', accumulator_result) # Window operator usage: running maximum within each partition stock_prices = db.stockPrices stock_prices.insert_many([ { "_id": 1, "ticker": "ABC", "hour": 1, "price": 50 }, { "_id": 2, "ticker": "ABC", "hour": 2, "price": 45 }, { "_id": 3, "ticker": "ABC", "hour": 3, "price": 60 }, { "_id": 4, "ticker": "ABC", "hour": 4, "price": 40 }, { "_id": 5, "ticker": "XYZ", "hour": 1, "price": 30 }, { "_id": 6, "ticker": "XYZ", "hour": 2, "price": 35 }, { "_id": 7, "ticker": "XYZ", "hour": 3, "price": 25 } ]) window_result = list(stock_prices.aggregate([ { "$setWindowFields": { "partitionBy": "$ticker", "sortBy": { "hour": 1 }, "output": { "highestSoFar": { "$max": "$price", "window": { "documents": ["unbounded", "current"] } } } } } ])) print('Window result:', window_result) client.close() example()